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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_quality_evidence_packet

Read-only

Return a full read-only quality evidence packet for a task: profile, declared checks, risk-based gate policy metadata, and the cross-provider quality reviewer contract. Scope checks by changed paths.

Instructions

READ-ONLY: full canonical evidence packet -- profile, declared checks, risk-based optional-gate policy metadata (not_available != passed), and the cross-provider read-only quality_reviewer contract.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aiworkhub_quality_evidence_packet"
  }
}

Input Schema

NameRequiredDescriptionDefault
changed_pathsNoRepository-relative paths changed by the task, recorded as affected_paths on each declared check; omit to leave the checks unscoped.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.67
    • addedInput schema / properties / changed_paths / description
      Added value: +"Repository-relative paths changed by the task, recorded as affected_paths on each declared check; omit to leave the checks unscoped."
  2. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description reinforces the read-only nature while adding non-obvious semantics: optional gates are risk-based and 'not_available != passed', which prevents a critical misinterpretation of missing gate data. It also flags that the reviewer contract is cross-provider and read-only. Limitations on output format are covered by the output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One front-loaded sentence starting with READ-ONLY, with every clause carrying substance (contents, gate caveat, contract). Slightly jargon-dense, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and the annotations plus the gate caveat cover the behavioral profile. What is missing is the routing rationale against sibling quality tools, which the single optional parameter would have been the natural place to anchor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single optional parameter changed_paths is fully documented in the schema, including that it maps to affected_paths on each check and that omitting it leaves checks unscoped. The description adds nothing about it, which is acceptable at this coverage level but earns only the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (a full canonical evidence packet) and enumerates its constituents: profile, declared checks, optional-gate policy metadata, and the quality_reviewer contract. It is clearly not a plain profile read. However, it never contrasts itself with near-siblings such as aiworkhub_quality_profile or aiworkhub_review_packet, so the agent must infer the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to call this versus alternatives, nor any prerequisite or exclusion. The words 'full canonical' hint that this is the complete variant of the evidence, but that is inference rather than guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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